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KFON to depend on Supplyco database to provide Internet connection to BPL families




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Hackathon in database technology to be held

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If 23andMe goes bust, what happens to its DNA database?

Millions of people have used 23andMe’s simple genetic testing service, which involves ordering a saliva test, spitting into a tube, and sending it back to the company for a detailed DNA analysis




database

Geochemical database of Cretaceous High Arctic Large Igneous Province magmatic rocks, Arctic Canada

Bédard, J H; Saumur, B -M; Williamson, M -C; Tegner, C; Troll, V R; Deegan, F M; Evenchick, C A; Grasby, S E; Dewing, K. Geological Survey of Canada, Open File 8759, 2020, 7 pages, https://doi.org/10.4095/327829
<a href="https://geoscan.nrcan.gc.ca/images/geoscan/gid_327829.jpg"><img src="https://geoscan.nrcan.gc.ca/images/geoscan/gid_327829.jpg" title="Geological Survey of Canada, Open File 8759, 2020, 7 pages, https://doi.org/10.4095/327829" height="150" border="1" /></a>




database

Northern Canada glacial geomorphology database 2020: part 1 - central mainland Nunavut

Behnia, P; McMartin, I; Campbell, J E; Godbout, P -M; Tremblay, T. Geological Survey of Canada, Open File 8717, 2020, 6 pages, https://doi.org/10.4095/327796
<a href="https://geoscan.nrcan.gc.ca/images/geoscan/gid_327796.jpg"><img src="https://geoscan.nrcan.gc.ca/images/geoscan/gid_327796.jpg" title="Geological Survey of Canada, Open File 8717, 2020, 6 pages, https://doi.org/10.4095/327796" height="150" border="1" /></a>




database

12C: IN DATABASE ARCHIVING

In this post, I will demonstrate a new feature introduced in 12c : In database archiving. It enables you to archive rows within a table by marking them as invisible. This is accomplshed  by means of a hidden column ORA_ARCHIVE_STATE. These invisible rows are not visible to the queries but if needed, can be viewed , by setting a session parameter ROW ARCHIVAL VISIBILITY.

Overview:

-- Create test user uilm, tablespace ilmtbs
-- Connect as user uilm
-- create and populate test table (5 rows) ilmtab with row archival clause
-- Note that the table has an additional column ORA_ARCHIVE_STATE automatically created   and has the default value of 0 (indicates that row is active)
-- Note that this column is not visible when we describe the table or simply issue select * from ...
-- We need to access data dictionary to view the column
-- Make two  rows in the table inactive by setting ORA_ARCHIVE_STATE column to a non zero value.
-- Check that inactive rows are not visible to query
-- Set the parameter ROW ARCHIVAL VISIBILITY  = all to see inactive rows also
-- Set the parameter ROW ARCHIVAL VISIBILITY  = active to hide inactive rows
-- Issue an insert into ... select * and check that only 3 visible rows are inserted
-- Set the parameter ROW ARCHIVAL VISIBILITY  = all to see inactive rows also
-- Issue an insert into ... select * and check that all the rows are inserted but ORA_ARCHIVE_STATE    is not propagated in inserted rows
-- Disable row archiving in the table and check that column ORA_ARCHIVE_STATE is automatically dropped
-- drop tablespace ilmtbs and user uilm

Implementation :

-- Create test user, tablespace and test table
SQL> conn sys/oracle@em12c:1523/pdb1 as sysdba
sho con_name

CON_NAME
------------------------------
PDB1

SQL> set sqlprompt PDB1>

PDB1>create tablespace ilmtbs datafile '/u02/app/oracle/oradata/cdb1/pdb1/ilmtbs01.dbf' size 1m;
grant connect, resource, dba  to uilm identified by oracle;
alter user uilm default tablespace ilmtbs;

conn uilm/oracle@em12c:1523/pdb1
sho con_name

CON_NAME
------------------------------
PDB1
-- create table with "row archival clause"
PDB1>drop table ilmtab purge;
create table ilmtab (id number, txt char(15)) row archival;
insert into ilmtab values (1, 'one');
insert into ilmtab values (2, 'two');
insert into ilmtab values (3, 'three');
insert into ilmtab values (4, 'four');
insert into ilmtab values (5, 'five');
commit;
-- Note that the table has an additional column ORA_ARCHIVE_STATE automatically created    and has the default value of 0 (indicates that row is active)
PDB1>col ora_archive_state for a20
select id, txt, ora_archive_state from ilmtab;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
1 one             0
2 two             0
3 three           0
4 four            0
5 five            0
-- Note that this column is not visible when we describe the table or simply issue select * from ...
PDB1>desc ilmtab
Name                                      Null?    Type
----------------------------------------- -------- ----------------------------
ID                                                 NUMBER
TXT                                                CHAR(15)

PDB1>select * from ilmtab;

ID TXT
---------- ---------------
1 one
2 two
3 three
4 four
5 five
-- Since the column is invisible, let me try and make it visible
-- Note that Since the column is maintained by oracle itself, user can't modify its attributes
PDB1>alter table ilmtab modify (ora_archive_state visible);
alter table ilmtab modify (ora_archive_state visible)
*
ERROR at line 1:
ORA-38398: DDL not allowed on the system ILM column
-- We need to access data dictionary to view the column
-- Note that this column is shown as hidden and has not been generated by user
PDB1>col hidden for a7
col USER_GENERATED for 20
col USER_GENERATED for a20

select TABLE_NAME, COLUMN_NAME, HIDDEN_COLUMN, USER_GENERATED
from user_tab_cols where table_name='ILMTAB';

TABLE_NAME  COLUMN_NAME          HID USER_GENERATED
----------- -------------------- --- --------------------
ILMTAB      ORA_ARCHIVE_STATE    YES NO
ILMTAB      ID                   NO  YES
ILMTAB      TXT                  NO  YES
-- We can make selected rows in the table inactive by setting ORA_ARCHIVE_STATE column to a non zero value.
This can be accomplished using update table... set ORA_ACRHIVE_STATE =
. <non-zero value>
. dbms_ilm.archivestatename(1)

-- Let's update row with id =1 with ORA_ARCHIVE_STATE=2
     and update row with id =2 with dbms_ilm.archivestatename(2)
PDB1>update ilmtab set ora_archive_state=2 where id=1;

update ilmtab set ora_archive_state= dbms_ilm.archivestatename(2) where id=2;
-- Let's check whether updates have been successful and hidden rows are not visible
PDB1>select id, txt, ORA_ARCHIVE_STATE from ilmtab;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
3 three           0
4 four            0
5 five            0
-- The updated rows are not visible!!
-- Quite logical since we have made the rows active and by default only active rows are visible

-- To see inactive rows also, we need to set the parameter ROW ARCHIVAL VISIBILITY  = all at session level
-- Note that the column ORA_ARCHIVE_STATE has been set to 1 for id =2 although we had set it to 2 using
dbms_ilm.archivestatename(2)
PDB1>alter session set ROW ARCHIVAL VISIBILITY  = all;
select id, txt, ORA_ARCHIVE_STATE from ilmtab;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
1 one             2
2 two             1
3 three           0
4 four            0
5 five            0
-- Note that the column ORA_ARCHIVE_STATE has been set to 1 for id =2 although we had set it to 2 using    dbms_ilm.archivestatename(2)

-- Let's find out why
-- Note that The function dbms_ilm.archivestatename(n) returns only two values    0 for n=0 and 1 for  n <> 0
PDB1>col state0 for a8
col state1 for a8
col state2 for a8
col state3 for a8

select dbms_ilm.archivestatename(0) state0 ,dbms_ilm.archivestatename(1) state1,
dbms_ilm.archivestatename(2) state2,dbms_ilm.archivestatename(3) state3  from dual;

STATE0   STATE1   STATE2   STATE3
-------- -------- -------- --------
0        1        1        1
-- In order to make the inactive rows (id=1,2) hidden again, we need to set the parameter ROW ARCHIVAL VISIBILITY  = Active
PDB1>alter session set row archival visibility = active;
select id, txt, ORA_ARCHIVE_STATE from ilmtab;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
3 three           0
4 four            0
5 five            0
-- Let's issue an insert into ... select *
-- Note that only 3 new rows are visible
PDB1>insert into ilmtab select * from ilmtab;

select id, txt, ora_archive_state from ilmtab;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
3 three           0
4 four            0
5 five            0
3 three           0
4 four            0
5 five            0

6 rows selected.
-- I want to check if hidden rows were also inserted
-- Let's check by making  hidden rows visible again
-- Note that only visible rows(id=3,4,5) were inserted
PDB1>alter session set row archival visibility=all;
select id, txt, ora_archive_state from ilmtab;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
1 one             2
2 two             1
3 three           0
4 four            0
5 five            0
3 three           0
4 four            0
5 five            0

8 rows selected.
-- Let's set row archival visibility = all and then again insert rows from ilmtab
-- Note that all the 8 rows are inserted but ORA_ARCHIVE_STATE ha not been copied    ORA_ARCHIVE_STATE <> 0 in only 2 records (id = 1,2) even now.
PDB1>alter session set row archival visibility=all;
insert into ilmtab select * from ilmtab;
select id, txt, ora_archive_state from ilmtab order by id;

ID TXT             ORA_ARCHIVE_STATE
---------- --------------- --------------------
1 one             0
1 one             2
2 two             0
2 two             1
3 three           0
3 three           0
3 three           0
3 three           0
4 four            0
4 four            0
4 four            0
4 four            0
5 five            0
5 five            0
5 five            0
5 five            0

16 rows selected.
-- Disable row level archiving for the table
-- Note that as soon as row archiving is disabled, pseudo column ora_archive_state is dropped automatically
PDB1>alter table ilmtab no row archival;
select id, txt, ORA_ARCHIVE_STATE from ilmtab;

ERROR at line 1:
ORA-00904: "ORA_ARCHIVE_STATE": invalid identifier

PDB1>col hidden for a7
col USER_GENERATED for 20
col USER_GENERATED for a20

select TABLE_NAME, COLUMN_NAME, HIDDEN_COLUMN, USER_GENERATED
from user_tab_cols where table_name='ILMTAB';

TABLE_NAME  COLUMN_NAME          HID USER_GENERATED
----------- -------------------- --- --------------------
ILMTAB      ID                   NO  YES
ILMTAB      TXT                  NO  YES
Note : Had we created this table using sys, we could not have disabled row archiving .

-- cleanup --
PDB1>conn sys/oracle@em12c:1523/pdb1 as sysdba
drop tablespace ilmtbs including contents and datafiles;
drop user uilm cascade;
References:

http://docs.oracle.com/cd/E16655_01/server.121/e17613/part_lifecycle.htm#VLDBG14154

----------------------------------------------------------------------------------------------------

Oracle 12c Index

----------------------------------------------------------------------------------------------

 




database

Are older releases of the database really unsupported?

articles: 

I see posts on Oracle related forums about various releases (anything that isn't 11.x or 12.x) being "unsupported". This is wrong. Of course you should upgrade any 9i or 10g databases, but you don't have to.

Oracle Corporation's lifetime support policy is documented here,
Lifetime Support Policy
take a look, and you'll see that release 10.2 was in premier support until end July 2010 when it went into extended support. At end July 2013, it goes into sustaining support. Sustaining support will continue indefinitely. Even release 8.1.7 will have sustaining support indefinitely.
So what is sustaining support? That is documented here,
Lifetime support benefits
To summarize, extended support gives you everything you are likely to need. What you do not get is certification against new Oracle products or new third party products (principally, operating systems). But does that matter? I don't think so. For example, release 11.2.0.3 (still in premier support) is not certified against Windows 8, but it works fine.
Sustaining support has a more significant problem: no more patches. Not even patches for security holes, or changes in regulatory requirements. The security patch issue may of course be serious, but regulatory issues are unlikely to matter (this is a database, not a tax management system.) Think about it: 10g has been around for many years. It is pretty well de-bugged by now. If you hit a problem with no work around, you are pretty unlucky. Sustaining support gives you access to technical support, available patches, software, and documentation. That is all most sites will ever need.
Right now, I am working on a 9.2.0.8 database. It cannot be upgraded because the application software is written by a company that does not permit a database upgrade. Why not? Well, the reason may be commercial: they have a replacement product that is supported on newer databases. But that is nothing to do with me. The database works, the software works. Making it work better is a challenge - but that is what a DBA is paid to do. Don't just write it off as "unsupported".
Of course I am not suggesting that users should not upgrade to current releases - but upgrades are a huge project, and can have major implications. Running out dated software is silly, unless you have an irrefutable reason for so doing. The lack of security patches make you vulnerable to data loss. The lack of regulatory patches may make it illegal. The lack of newer facilities will be restricting the utility of the system. You may be losing money by not taking of advantage of changes of newer technology that can better exploit your hardware.
If anyone is looking for consulting support to upgrade their database - my boss will be happy to give you a quote. But I won't refuse to support you in the meantime.
--
John Watson
Oracle Certified Master DBA
http://skillbuilders.com




database

Niche Database by Frank Mullen

#1 Niche Marketing Software For Small Business Ideas



  • Business -- Promotion


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Database Security: What Students Need to Know




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Automatic Grading of Spreadsheet and Database Skills




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A Database Practicum for Teaching Database Administration and Software Development at Regis University




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Implementing Team-Based Learning: Findings From a Database Class

Aim/Purpose: The complexity of today’s organizational databases highlights the importance of hard technical skills as well as soft skills including teamwork, communication, and problem-solving. Therefore, when teaching students about databases it follows that using a team approach would be useful. Background: Team-based learning (TBL) has been developed and tested as an instructional strategy that leverages learning in small groups in order to achieve increased overall effectiveness. This research studies the impact of utilizing team-based learning strategies in an undergraduate Database Management course in order to determine if the methodology is effective for student learning related to database technology concepts in addition to student preparation for working in database teams. Methodology: In this study, a team-based learning strategy is implemented in an undergraduate Database Management course over the course of two semesters. Students were assessed both individually and in teams in order to see if students were able to effectively learn and apply course concepts on their own and in collaboration with their team. Quantitative and qualitative data was collected and analyzed in order to determine if the team approach improved learning effectiveness and allowed for soft skills development. The results from this study are compared to previous semesters when team-based learning was not adopted. Additionally, student perceptions and feedback are captured. Contribution: This research contributes to the literature on database education and team-based learning and presents a team-based learning process for faculty looking to adopt this methodology in their database courses. This research contributes by showing how the collaborative assessment aspect of team-based learning can provide a solution for the conceptual and collaborative needs of database education. Findings: Findings related to student learning and perceptions are presented illustrating that team-based learning can lead to improvements in performance and provides a solution for the conceptual and collaborative needs of database education. Specifically, the findings do show that team scores were significantly higher than individual scores when completing class assessments. Student perceptions of both their team members and the team-based learning process were overall positive with a notable difference related to the perception of team preparedness based on gender. Recommendations for Practitioners: Educational implications highlight the challenges of team-based learning for assessment (e.g., gender differences in perceptions of team preparedness), as well as the benefits (e.g., development of soft skills including teamwork and communication). Recommendation for Researchers: This study provides research implications supporting the study of team assessment techniques for learning and engagement in the context of database education. Impact on Society: Faculty looking to develop student skills in relation to database concepts and application as well as in relation to teamwork and communication may find value in this approach, ultimately benefiting students, employers, and society. Future Research: Future research may examine the methodology from this study in different contexts as well as explore different strategies for group assignments, room layout, and the impact of an online environment.




database

Research on fast mining of enterprise marketing investment databased on improved association rules

Because of the problems of low mining precision and slow mining speed in traditional enterprise marketing investment data mining methods, a fast mining method for enterprise marketing investment databased on improved association rules is proposed. First, the enterprise marketing investment data is collected through the crawler framework, and then the collected data is cleaned. Then, the cleaned data features are extracted, and the correlation degree between features is calculated. Finally, according to the calculation results, all data items are used as constraints to reduce the number of frequent itemsets. A pruning strategy is designed in advance. Combined with the constraints, the Apriori algorithm of association rules is improved, and the improved algorithm is used to calculate all frequent itemsets, Obtain fast mining results of enterprise marketing investment data. The experimental results show that the proposed method is fast and accurate in data mining of enterprise marketing investment.




database

A Data Model Validation Approach for Relational Database Design Courses




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Restructuring an Undergraduate Database Management Course for Business Students




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Design, Development and Deployment Considerations when Applying Native XML Database Technology to the Programme Management Function of an SME




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Complexity of Social Interactions in Collaborative Learning: The Case of Online Database Environment




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